Battery Simulation & Computational Scientist Internship

About the role#

Sila Nanotechnologies is seeking a Battery Simulation & Computational Scientist Intern to bridge the gap between theoretical electrochemical equations and production-grade software code. This role focuses on leveraging physics-based models to accelerate learning cycles and reduce the cost of empirical research and development. The position is available on a rolling basis for a duration of at least 6 months and can be performed remotely or on-site.

What you'll do#

• Architect and implement physics-based battery models using PyBaMM.
• Analyze electrochemical data to build, parameterize, and apply new numerical models.
• Fit electrochemical models to experimental data and evaluate performance across various test techniques.
• Support infrastructure development by building backend pipelines and tools to scale the use of physics-based models.
• Collaborate with scientists and cross-functional teams to discover and communicate insights for the development of next-generation battery materials.

What you'll need#

• BSc, MSc, or Ph.D. in Computer Science, Applied Mathematics, Chemical Engineering, Materials Science, or a related field.
• Strong experience using PyBaMM (Python Battery Mathematical Modeling).
• Mastery of Python, including scientific libraries such as NumPy, SciPy, and Pandas.
• Experience interacting with databases using SQL or Snowflake.
• Knowledge of electrochemical theory and the application of P2D (Pseudo-Two-Dimensional) or Doyle-Fuller-Newman models.
• Proficiency with Git, Linux or macOS terminal environments, and collaboration platforms like GitHub or GitLab.
• Experience with CI/CD pipelines, containerization (Docker), or full-stack development is preferred.
• Experience with AI coding tools and effective prompting techniques.

Location & details#

• Location: Alameda, California (Remote or On-site).
• Status: Full-time, paid internship.
• Term: Rolling (minimum 6-month commitment).